
# IMPORTS

# since this notebook lives in a sub-folder of the main project, I'll add the main folder to the python path
import sys
sys.path.append("../")

# Load my module
from tools.glooko import read_all

# Load extra stuff that I need
import numpy as np
import pandas as pd

# Plotting (matplotlib widge allows for interactivity in the live notebook)
import matplotlib.pyplot as plt
%matplotlib widget


# GET UNIQUE DAYS

# I added a new module, stats.py, to the tools package. So far it 
# contains a function to extract unique days
from tools.stats import get_yeardays

df_cgm, df_bolus, df_basal, df_insulin = read_all(r"../data")
df_cgm["yearday"] = get_yeardays(df_cgm)
df_insulin["yearday"] = get_yeardays(df_insulin)

# COMPUTE STATS PER DAY
df_cgm.drop("sn_cgm", axis=1, inplace=True)
df_cgm_summary = df_cgm[["bg", "yearday"]].groupby("yearday").describe()["bg"]


df_cgm_summary["yearday"] = df_cgm_summary.index
df_cgm_summary["time"] = pd.to_datetime(df_cgm_summary['yearday'], format='%Y-%j')


import plotly.graph_objects as go
import plotly.express as px
from plotly.subplots import make_subplots


fig = make_subplots(rows=2, cols=1, vertical_spacing = 0.05)

fig.add_trace(go.Scatter(
    name="Mean BG",
    mode="markers", x=df_cgm_summary["time"], y=df_cgm_summary["mean"]
), row=1, col=1)

fig.add_trace(go.Scatter(
    name="75th",
    mode="lines", x=df_cgm_summary["time"], y=df_cgm_summary["75%"],
), row=1, col=1)

fig.add_trace(go.Scatter(
    name="25th",
    mode="lines", x=df_cgm_summary["time"], y=df_cgm_summary["25%"],
), row=1, col=1)

fig.add_trace(go.Scatter(
    name="Total",
    mode="lines", x=df_insulin["time"], y=df_insulin["total_insulin"],
), row=2, col=1)

fig.add_trace(go.Scatter(
    name="Basal",
    mode="lines", x=df_insulin["time"], y=df_insulin["total_basal"],
), row=2, col=1)

fig.update_layout(height=600)

fig.update_xaxes(showticklabels=False) # hide all the xticks
fig.update_xaxes(showticklabels=True, row=2, col=1)

fig.update_xaxes(matches='x')

fig.show()


import seaborn as sns
from matplotlib.patches import Rectangle

fig, ax = plt.subplots(2,1,figsize=(8, 7), sharex=True)

# Plot the insulin
sns.set_color_codes("pastel")
sns.barplot(x="time", y="total_insulin", data=df_insulin,
            label="Bolus/Correction", color="b", ax=ax[0])

# Plot the basal 
sns.set_color_codes("muted")
sns.barplot(x="yearday", y="total_basal", data=df_insulin,
            label="Basal", color="b", ax=ax[0])

# Add a legend and informative axis label
ax[0].legend(ncol=1, frameon=True)
sns.despine(left=True, bottom=True,ax=ax[0])

# BOX PLOTS
sns.boxplot(x="yearday", y="bg",data=df_cgm,
            whis=[0, 100], width=.7, ax=ax[1])

# Add rectangle
xmin = ax[1].get_xticks()[0]
xmax = ax[1].get_xticks()[-1]
goal_range = Rectangle((xmin, 70),xmax-xmin, 180-70, color ='gray', alpha=0.25,zorder=0)
ax[1].add_patch(goal_range)

ax[1].xaxis.grid(True)
sns.despine(trim=True, left=True)

ax[0].set_xlabel("")
ax[1].set_xlabel("Day")
ax[1].tick_params(rotation=50)
ax[1].invert_xaxis()


fig.tight_layout()

TL;DR¶

Plotting daily BGs and insulin summaries using Plotly¶

Back to seaborn¶